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arXiv · 2502.17584

Gaussian Process-Based Scalar Field Estimation in GPS-Denied Environments

Muzaffar Qureshi·Tochukwu Elijah Ogri·Humberto Ramos·Zachary I. Bell·Rushikesh Kamalapurkar
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Abstract

This paper presents a methodology for an autonomous agent to map an unknown scalar field in GPS-denied regions. To reduce localization errors, the agent alternates between GPS-enabled and GPS-denied areas while collecting measurements. User-defined error bounds determine the dwell time in each region. A switching trajectory is then designed to ensure field measurements in GPS-denied regions remain within the specified error limits. A Lyapunov-based stability analysis guarantees bounded error trajectories while tracking the desired path. The effectiveness of the proposed methodology is demonstrated through simulations, with an error analysis comparing the GP-predicted scalar field model to the actual field.

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Muzaffar Qureshi, Tochukwu Elijah Ogri, Humberto Ramos, Zachary I. Bell, Rushikesh Kamalapurkar. 2025-02-24. Gaussian Process-Based Scalar Field Estimation in GPS-Denied Environments. https://arxiv.org/abs/2502.17584

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